U.S. patent number 9,734,603 [Application Number 15/282,419] was granted by the patent office on 2017-08-15 for systems and methods for peak tracking and gain adjustment.
This patent grant is currently assigned to General Electric Company. The grantee listed for this patent is General Electric Company. Invention is credited to Tuoyu Cao, Mark David Fries, Floribertus P. M. Heukensfeldt Jansen.
United States Patent |
9,734,603 |
Heukensfeldt Jansen , et
al. |
August 15, 2017 |
Systems and methods for peak tracking and gain adjustment
Abstract
A radiation detection system includes a detector unit and at
least one processor. The detector unit is configured to generate
signals responsive to radiation. The at least one processor is
operably coupled to the detector unit and configured to receive the
signals from the detector unit. The at least one processor is
configured to obtain, during an imaging process, a first count for
at least one of the signals corresponding to a first intrinsic
energy window, the first energy window corresponding to values
higher than an intrinsic peak value; obtain a second count for the
at least one of the signals corresponding to a second intrinsic
energy window, the second energy window corresponding to values
lower than the intrinsic peak value; and adjust a gain applied to
the signals based on at least the first count and the second
count.
Inventors: |
Heukensfeldt Jansen; Floribertus P.
M. (Niskayuna, NY), Fries; Mark David (Waukesha, WI),
Cao; Tuoyu (Waukesha, WI) |
Applicant: |
Name |
City |
State |
Country |
Type |
General Electric Company |
Schenectady |
NY |
US |
|
|
Assignee: |
General Electric Company
(Schenectady, NY)
|
Family
ID: |
57776209 |
Appl.
No.: |
15/282,419 |
Filed: |
September 30, 2016 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20170018099 A1 |
Jan 19, 2017 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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14755536 |
Jun 30, 2015 |
9508165 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01T
1/40 (20130101); G06T 11/005 (20130101); G06T
11/008 (20130101); G01T 1/17 (20130101); G06K
9/0053 (20130101) |
Current International
Class: |
G06K
9/00 (20060101); G06T 11/00 (20060101); G01T
1/17 (20060101); G01T 1/40 (20060101) |
Field of
Search: |
;382/162-167 |
References Cited
[Referenced By]
U.S. Patent Documents
Other References
Conti et al.; Monitoring Energy Calibration Drift Using the
Scintillator Background Radiation; IEEE Transactions on Nuclear
Science; vol. 58, No. 3; Jun. 2011; 8 pages. cited by
applicant.
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Primary Examiner: Liew; Alex
Attorney, Agent or Firm: Small; Dean D. The Small Patent Law
Group, LLC
Parent Case Text
RELATED APPLICATIONS
The present application claims priority to and is a continuation in
part of U.S. patent application Ser. No. 14/755,536, filed 30 Jun.
2015, entitled "Systems and Methods for Peak Tracking and Gain
Adjustment," the subject matter of which is hereby incorporated by
reference in its entirety.
Claims
What is claimed is:
1. A radiation detection system comprising: a detector unit
comprising a scintillator block and a photosensor, the detector
unit configured to generate signals responsive to radiation; and at
least one processor operably coupled to the detector unit and
configured to receive the signals from the detector unit, the at
least one processor configured to: obtain, during an imaging
process, at least a first count for at least one of the signals
corresponding to a first intrinsic energy window, the first energy
window corresponding to values higher than an intrinsic peak value;
obtain, during the imaging process, at least a second count for the
at least one of the signals corresponding to a second intrinsic
energy window, the second energy window corresponding to values
lower than the intrinsic peak value; and adjust a gain applied to
the signals based on at least the first count and the second
count.
2. The radiation detection system of claim 1, wherein the at least
one processor is further configured to: obtain received radiation
counts for the at least one of the signals corresponding to windows
associated with a received energy portion of the at least one of
the signals; and adjust the gain based on the first count, the
second count, and the received radiation counts for the windows
associated with the received energy portion.
3. The radiation detection system of claim 1, wherein the at least
one processor is further configured to: obtain a third count for
the at least one of the signals corresponding to a third intrinsic
energy window; obtain a fourth count for the at least one of the
signals corresponding to a fourth intrinsic energy window; obtain a
fifth count for the at least one of the signals corresponding to a
first received energy window; obtain a sixth count for the at least
one of the signals corresponding to a second received energy
window; obtain a seventh count for the at least one of the signals
corresponding to a third received energy window; obtain an eighth
count for the at least one of the signals corresponding to a fourth
received energy window; and adjust the gain applied to the signals
based on a weighted sum of the first count, the second count, the
third count, the fourth count, the fifth count, the sixth count,
the seventh count, and the eighth count.
4. The radiation detection system of claim 2, wherein the at least
one processor is further configured to: obtain an auxiliary count
for the at least one of the signals corresponding to an auxiliary
window; adjust the gain based on the first count, the second count,
and the auxiliary count.
5. The radiation detection system of claim 2, wherein the at least
one processor is further configured to: adjust the gain using the
first count and the second count during an initial start-up period;
and adjust the gain using the first count, the second count, and
the counts for the windows associated with the received energy peak
during an imaging period.
6. The radiation detection system of claim 2, wherein the at least
one processor is configured to select an adjustment technique based
on a peak analysis metric, wherein the peak analysis metric is
based on a weighted sum of windows around a given peak.
7. The radiation detection system of claim 6, wherein the at least
one processor is configured to select between a coarse adjustment
technique and a fine adjustment technique.
8. The radiation detection system of claim 1, wherein the at least
one processor is configured to adjust the gain virtually by
adjusting measured values received from the detector unit.
9. The radiation detection system of claim 1, wherein the at least
one processor is configured to determine a stability metric, and to
determine whether or not to adjust the gain based on the stability
metric.
10. A method comprising: generating signals, with a detector unit,
responsive to radiation; obtaining, with at least one processor,
during an imaging process, a first count for at least one of the
signals corresponding to a first intrinsic energy window, the first
energy window corresponding to values higher than an intrinsic peak
value; obtaining, with the at least one processor, during the
imaging process, a second count for the at least one of the signals
corresponding to a second intrinsic energy window, the second
energy window corresponding to values lower than the intrinsic peak
value; and adjusting a gain applied to the signals based on at
least the first count and the second count.
11. The method of claim 10, further comprising: obtaining received
radiation counts for the at least one of the signals corresponding
to windows associated with a received energy portion of the at
least one of the signals; and adjusting the gain based on the first
count, the second count, and the received radiation counts for the
windows associated with the received energy portion.
12. The method of claim 11, further comprising: adjusting the gain
using the first count and the second count during an initial
start-up period; and adjusting the gain using the first count, the
second count, and the counts for the windows associated with the
received energy peak during an imaging period.
13. The method of claim 11, further comprising selecting an
adjustment technique based on a peak analysis metric, wherein the
peak analysis metric is based on a weighted sum of windows around a
given peak.
14. The method of claim 13, further comprising selecting between a
coarse adjustment technique and a fine adjustment technique.
15. The method of claim 10, wherein the gain is adjusted virtually
by adjusting measured values received from the detector unit.
16. The method of claim 10, further comprising determining a
stability metric, and determining whether or not to adjust the gain
based on the stability metric.
17. A tangible and non-transitory computer readable medium
comprising one or more software modules configured to direct one or
more processors to: generate signals, with a detector unit,
responsive to radiation; obtain, during an imaging process, a first
count for at least one of the signals corresponding to a first
intrinsic energy window, the first energy window corresponding to
values higher than an intrinsic peak value; obtain, during an
imaging process, a second count for the at least one of the signals
corresponding to a second intrinsic energy window, the second
energy window corresponding to values lower than the intrinsic peak
value; and adjust a gain applied to the signals based on at least
the first count and the second count.
18. The tangible and non-transitory computer readable medium of
claim 17, wherein the one or more software modules are further
configured to direct the one or more processors to: obtain counts
for the at least one of the signals corresponding to windows
associated with a received energy portion of the at least one of
the signals; and adjust the gain based on the first count, the
second count, and the counts for the windows associated with the
received energy portion.
19. The tangible and non-transitory computer readable medium of
claim 17, wherein the one or more software modules are further
configured to direct the one or more processors to: adjust the gain
virtually by adjusting measured values received from the detector
unit.
20. The tangible and non-transitory computer readable medium of
claim 17, wherein the one or more software modules are further
configured to direct the one or more processors to: determine a
stability metric; and determine whether or not to adjust the gain
based on the stability metric.
Description
BACKGROUND OF THE INVENTION
The subject matter disclosed herein relates generally to imaging
systems and techniques, and more particularly to energy spectrum
analysis and gain adjustment.
In certain types of imaging devices, such as positron emission
tomography (PET) scanners, arrays of detector elements are used to
detect radiation emanating from the patient. In a PET scanner, for
example, arrays of scintillator crystals may be used to detect
annihilation photons which are generated inside the patient. The
annihilation photons are produced when a positron emitted from a
radiopharmaceutical injected into the patient collides with an
electron causing an annihilation event. The scintillator crystals
receive the annihilation photons and generate light photons in
response to the annihilation photons, with the light photons
detected by a photosensor configured to convert the light energy
from the light photons to electrical energy used to reconstruct an
image.
Detector behavior (e.g., detector gain), however, may vary over
time. Detector gain depends, among other things, on the temperature
of various components as well as a bias voltage applied to a
silicon photomultiplier (SiPM). As the detector gain varies, the
energy peak for detected events varies, reducing accuracy.
Conventionally, peak stability as a function of temperature may be
controlled using a thermal monitoring system, and used to adjust
the gain based on the temperature. Such approaches work to an
extent, but may not provide a desired level of peak stability or
accuracy of gain adjustment. Peak instability may be a particular
concern in PET systems used in conjunction with magnetic resonance
imaging (MRI), as activation of gradient coils of an MRI system may
result in relatively larger and/or quick increases in
temperature.
BRIEF DESCRIPTION OF THE INVENTION
In accordance with various embodiments, a radiation (e.g., positron
emission tomography (PET)) detection system that includes a
detector unit and at least one processor is provided. The detector
unit is configured to generate signals responsive to radiation. The
at least one processor is operably coupled to the detector unit and
configured to receive the signals from the detector unit. The at
least one processor is configured to obtain a first count for at
least one of the signals corresponding to a first intrinsic energy
window, the first energy window corresponding to values higher than
an intrinsic peak value; obtain a second count for the at least one
of the signals corresponding to a second intrinsic energy window,
the second energy window corresponding to values lower than the
intrinsic peak value; and adjust a gain applied to the signals
based on the first count and the second count. As used herein,
intrinsic energy may be understood as energy that is not received
from an object being imaged. For example, intrinsic energy may be
due to radioactivity within a detector crystal. As another example,
in some embodiments, intrinsic energy may be provided from another
source (other than the object being imaged).
In accordance with various embodiments, a method is provided that
includes generating signals, with a detector unit, responsive to
radiation. The method also includes obtaining, with at least one
processor, a first count for at least one of the signals
corresponding to a first intrinsic energy window, with the first
energy window corresponding to values higher than an intrinsic peak
value. The method also includes obtaining, with the at least one
processor, a second count for the at least one of the signals
corresponding to a second intrinsic energy window, with the second
energy window corresponding to values lower than the intrinsic peak
value. Further, the method includes adjusting a gain applied to the
signals based on the first count and the second count.
In accordance with various embodiments, a tangible and
non-transitory computer readable medium is provided that includes
one or more software modules. The one or more software modules are
configured to direct one or more processors to generate signals,
with a detector unit, responsive to radiation; obtain, a first
count for at least one of the signals corresponding to a first
intrinsic energy window, the first energy window corresponding to
values higher than an intrinsic peak value; obtain a second count
for the at least one of the signals corresponding to a second
intrinsic energy window, the second energy window corresponding to
values lower than the intrinsic peak value; and adjust a gain
applied to the signals based on the first count and the second
count.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a schematic diagram of a PET detection system in
accordance with various embodiments.
FIG. 2 is a plan view of a crystal array of the PET detection
system of FIG. 1.
FIG. 3A depicts histograms corresponding to signals from elements
of a crystal array in accordance with various embodiments.
FIG. 3B depicts scaled histograms using the histograms of FIG.
3A.
FIG. 3C depicts a combined histogram using the scaled histograms of
FIG. 3B.
FIG. 4 depicts example windows used in connection with various
embodiments.
FIG. 5 depicts example windows used in connection with various
embodiments.
FIG. 6 is a flowchart of a method in accordance with various
embodiments.
FIG. 7 illustrates an imaging system in accordance with various
embodiments.
FIG. 8 is a schematic diagram of the imaging system of FIG. 7.
FIG. 9 illustrates an example of a detector module which forms part
of the imaging system in accordance with various embodiments.
FIG. 10 depicts example windows used in connection with various
embodiments.
FIG. 11 is a flowchart of a method in accordance with various
embodiments.
FIG. 12 is a flowchart of a method in accordance with various
embodiments.
DETAILED DESCRIPTION OF THE INVENTION
The following detailed description of certain embodiments will be
better understood when read in conjunction with the appended
drawings. To the extent that the figures illustrate diagrams of the
functional blocks of various embodiments, the functional blocks are
not necessarily indicative of the division between hardware
circuitry. Thus, for example, one or more of the functional blocks
(e.g., processors or memories) may be implemented in a single piece
of hardware (e.g., a general purpose signal processor or random
access memory, hard disk, or the like) or multiple pieces of
hardware. Similarly, the programs may be stand-alone programs, may
be incorporated as subroutines in an operating system, may be
functions in an installed software package, may be implemented in
hardware or firmware, and the like. It should be understood that
the various embodiments are not limited to the arrangements and
instrumentality shown in the drawings.
As used herein, the terms "system," "unit," and "module" include a
hardware and/or software system that operates to perform one or
more functions. For example, a system, unit, or module may include
electronic circuitry that includes and/or is coupled to one or more
computer processors, controllers, or other logic based devices that
perform operations based on instructions stored on a tangible and
non-transitory computer readable storage medium, such as a computer
memory. Alternatively or additionally, a system, unit, or module
may include a hard-wired device that performs operations based on
hard-wired logic of the device. The systems, units, or modules
shown in the attached figures may represent the hardware that
operates based on software or hardwired instructions, the software
that directs hardware to perform the operations, or a combination
thereof. "Systems," "units," or "modules" may include or represent
hardware and associated instructions (e.g., software stored on a
tangible and non-transitory computer readable storage medium, such
as a computer hard drive, ROM, RAM, or the like) that perform one
or more operations described herein. The hardware may include
electronic circuits that include and/or are connected to one or
more logic-based devices, such as microprocessors, processors,
controllers, or the like. These devices may be off-the-shelf
devices that are appropriately programmed or instructed to perform
operations described herein from the instructions described herein.
Additionally or alternatively, one or more of these devices may be
hard-wired with logic circuits to perform these operations.
Further, "systems," "units," or "modules" may be configured to
execute one or more algorithms to perform functions or operations
described herein. The one or more algorithms may include aspects of
embodiments disclosed herein, whether or not expressly identified
in a flowchart or as a step of a method.
As used herein, an element or step recited in the singular and
proceeded with the word "a" or "an" should be understood as not
excluding plural of said elements or steps, unless such exclusion
is explicitly stated. Furthermore, references to "one embodiment"
are not intended to be interpreted as excluding the existence of
additional embodiments that also incorporate the recited features.
Moreover, unless explicitly stated to the contrary, embodiments
"comprising" or "having" an element or a plurality of elements
having a particular property may include additional such elements
not having that property.
Various embodiments provide PET photosensor and/or PET detector
systems with improved gain stability. In various embodiments,
singles events may be examined at the detector front end, in
multiple energy windows including windows near the peak, to detect
small peak shifts accurately. The energy windows may be fixed or
scalable. By counting singles events that fall into each window, it
may be determined if the peak has shifted from a nominal or target
peak value (e.g., 511 keV for annihilation photons). If the peak
differs from the target peak by more than a predetermined amount
(in some embodiments, the predetermined amount may be fixed, while
in others the predetermined amount may be scalable), the gain of a
corresponding photodetector device may be appropriately
adjusted.
Various embodiments may be implemented in programmable hardware on
a detector board, with the window sizes and gain transfer function
represented by configurable logic (e.g., registers, state machines,
mathematical functions). Alternatively, firmware that executes on a
detector acquisition board may sample energy peak locations of
single event data and perform similar window counting and gain
transfer functions.
In various embodiments, 3 or more windows are used to analyze
signals (e.g., as represented by histograms sorted by energy
level). For instance, in an example embodiment having a target or
nominal peak value of 511 keV, four windows may be used in for each
detection unit of a PET system--a scatter window (having energy
levels between 460-480 keV), a lower window (having energy levels
between 480-510 keV), an upper window (having energy levels between
512-542 keV), and a background window (having energy levels between
542-562 keV).
For the example embodiment, the energy of singles events processed
are first corrected or adjusted based on known or expected gains,
such as by using a lookup table based on the crystal location. The
energy is then compared to the energy windows and used to increment
the appropriate counter for events that fall within one of the
windows. As the window counters are incremented, a running total
may be obtained that is equal to WU-WL+A*WS-B*WB, where the running
total is a peak tracking metric, WU is the number of counts for the
upper window, WL is the number of counts for the lower window, WS
is the number of counts in the scatter window, WB is the number of
counts in the background window, and A and B are scaling or
weighting factors applied to the scatter counts and the background
counts, respectively. The values of A and B may be experimentally
determined during a calibration process (e.g., a calibration of a
representative model of detector unit, with the experimentally
determined values utilized for detector units having the same
components and configuration). In some embodiments, a gain transfer
function may be implemented by determining when the running total
reaches a threshold, for example 200, and defining another counter
(e.g., a voltage offset counter) that is then incremented or
decremented (depending on whether the running total difference is
positive or negative). It may be noted that, in some embodiments, a
conventional thermal update gain algorithm may be run with peak
tracking, and any gain update determined using peak tracking may be
foregone if there is to be an adjustment based on thermal drift,
for example to help eliminate or reduce overshoot. It may be noted
that additional or alternative windows and weighting factors may be
used for isotopes that introduce additional peaks and shape in an
energy spectrum (also known as "dirty isotopes").
Accordingly, various embodiments improve peak stability by
providing improved accuracy and reliability in gain adjustment
(e.g., to help address environmental changes, such as increases or
decreases in temperature, or changes in the supply voltage). By
improving peak stability, tighter energy windows may be used in
identifying singles events for a high precision mode of operation
that gives greater noise equivalent count rate (NECR) capability,
lower scatter fraction, and so better image quality, while being
more quantitative than certain current approaches.
A technical effect of at least some embodiments provides improved
detector performance. For example, a technical effect of at least
some embodiments includes improved accuracy of gain adjustment and
peak stability. As another example, a technical effect of at least
some embodiments provides improved detector count rate linearity. A
technical effect of at least some embodiments provides improved
signal to noise ratio in patient images (e.g., by reducing the
effects of scatter). A technical effect of at least some
embodiments provides improved quantitative accuracy (e.g., due to
reduced peak drift).
FIG. 1 provides a schematic diagram of a radiation detection system
100 (e.g., PET detection system 100) formed in accordance with
various embodiments. The depicted PET detection system 100 includes
a detector unit 105 and a processing unit 130. It may be noted that
one or more aspects of the detector unit 105 and the processing
unit 130 may be integrally formed or otherwise disposed in a common
housing. For example, photosensors of the detector unit 105 and
aspects of the processing circuitry of the processing unit may be
disposed on a common chip. Additionally or alternatively, aspects
of the processing unit 130 may be part of an FPGA or ASIC that is
mounted to the detector unit 105 and communicably coupled to the
detector unit 105. Generally, the PET detection system 100 is
configured to receive a photon or gamma ray, and provide an output
(e.g., signals 108) indicative of the energy of the gamma ray, the
location of impact of the gamma ray, and the timing of the impact
of the gamma ray to a reconstruction processing unit 140 that is
disposed off-board of the detector unit 105. The reconstruction
processing unit may then use the information from the PET detection
system 100 and other generally similar PET detection systems
disposed about an object to be imaged to reconstruct an image of at
least a portion of the object to be imaged. It may be noted that,
in various embodiments, one or more aspects of the processing unit
130 may be disposed on the off-board reconstruction processing unit
140. It may further be noted that the PET detection system is one
example of a radiation detection system, and the other types of
detection systems may be utilized in various embodiments. For
example, in some embodiment, a direct conversion radiation
detection system or detection system utilizing direct conversion
devices may be employed.
The depicted detector unit 105 includes a crystal array 110, a
light guide 112, and a photosensor unit 120. Generally, an
annihilation photon 106 impacts the crystal array 110, and the
crystal array generates light photons 107 responsive to the
annihilation photon 106. The light photons 107 impact the
photosensor unit 120, which provides signals 108 corresponding to
the reception of the light photons 107. Signals 108 corresponding
to annihilation photon or gamma ray impact on the various crystals
may be used to determine the energy and location of impacts, which
may be used to reconstruct the image. It may be noted that each
photon impact may also be referred to as a radiation event. For
example, a given annihilation photon impact may be a singles event.
Two opposed singles events on a common line of response within a
predetermined time range of each other may be determined to
correspond to a coincidence event, with the coincidence events used
to reconstruct an image.
The depicted crystal array 110 is configured to be impacted by
gamma rays or photons during a PET scan and to produce light in
response to being impacted by gamma rays or photons. The crystal
array 110 is an example of a scintillator block that produces light
in response to the impact of gamma rays or photons. The light may
be detected by an associated photosensor (e.g. Silicon
photomultiplier (SiPM)) and used to reconstruct an image. The
crystal array 110 may be formed, for example, from a group of
crystals, with one or more internal light barriers between groups
of crystals. For ease of illustration and clarity of description,
it may be noted that only one crystal array 110 and only one PET
detection system 100 are shown in FIG. 1. It may be noted that, in
practice, multiple generally similar PET detection systems 100 may
be disposed about an object being imaged (e.g., in a ring), with
photons from a given annihilation event striking opposite crystal
arrays or detection systems 100. The particular numbers and/or
arrangement of detections systems, crystals, and photosensors
(and/or photosensor regions) for the various embodiments depicted
and/or discussed herein are provided by way of example. Other
numbers and/or arrangements may be employed in various
embodiments.
As best seen in FIG. 2, the depicted crystal array 110 includes a
number of crystals 114 arranged in sub-arrays. In the illustrated
embodiment, sub-array 116 includes a 3.times.4 group of crystals or
blocks, and sub-array 117 includes a different 3.times.4 group of
crystals or blocks. Different numbers of crystals may be arranged
into sub-arrays in various embodiments. In some embodiments, each
sub-array of the crystal array 110 has a dedicated or corresponding
photosensor region of the photosensor unit 120 assigned thereto.
Accordingly, light from each sub-array may be independently
detected or identified. Further, each photosensor region may have
an independently adjustable voltage supplied thereto. Accordingly,
the voltage and/or gain associated with a given corresponding
photosensor and sub-array may be adjusted independently of the
voltage and/or gain of other photosensor/sub-array
combinations.
The light guide 112 is disposed between the crystal array 110 and
the photosensor unit 120. The light guide 112 is configured to
direct light from the crystal array 110 (e.g., light generated in
response to the impact of annihilation photons on the crystal array
110) to the photosensor unit 120. The light guide 112, for example,
may be made of plastic or glass. Generally, the light guide 112 may
be configured to have a refractive index that is close to the
refractive index of the crystal array 110 or close to the
refractive index of the photosensor unit 120 to help in the
transfer of light from the crystal array 110 to the photosensor
unit 120. In some embodiments in which the photosensor unit 120 is
directly coupled to the crystal array 110, optical epoxy may be
utilized without a lightguide. In some embodiments, the light guide
112 may be beveled (e.g., has a larger cross-section proximate to
the crystal array 110 than proximate to the photosensor unit 120).
Thus, the area and/or number of photosensors may be reduced,
thereby reducing the cost, capacitance, and noise (dark
current).
The depicted photosensor unit 120 is configured to receive, via the
light guide 112, light generated by the crystal array 110, and to
provide an electrical charge or output (e.g., one or more signals
108 to the processing unit 130) responsive to the received light.
The photosensor unit 120 of the illustrated embodiment includes a
first photosensor region 121, and a second photosensor region 122.
Additional photosensor regions may be employed in various
embodiments. Each photosensor region may correspond to or be
dedicated to one or more sub-arrays of the crystal array 110. For
example, the first photosensor region 121 may correspond to the
sub-array 116, and the second photosensor region 122 may correspond
to the sub-array 117. Each photosensor region may have an
independently adjustable voltage provided thereto, so that the gain
associated with each photosensor (and associated portions of the
crystal array 110) may be independently adjusted.
In various embodiments, each photosensor region is separated from
the other photosensor regions by light barriers. Each photosensor
region may be operably coupled to a corresponding regional circuit
portion and provide an output to the corresponding regional circuit
portion. In some embodiments, the photosensor regions each include
plural photosensor units. The number of photosensor units in some
embodiments may correspond to the number of crystal elements in a
corresponding sub-array, while in other embodiments the numbers may
differ. It may be noted that other numbers and/or arrangements of
photosensor regions and/or crystal portions may be used in various
embodiments. In some embodiments, each photosensor region may have
only a single photosensor unit associated therewith.
Generally, each photosensor region provides an independent output
(e.g., independent of other photosensor regions) signal (or
signals) unique to that region and corresponding to the impact of
gamma rays or photons on a portion of the crystal array associated
with the particular region. It may be noted that a given gamma ray
may result in an output from more than one photosensor region, for
example due to Compton scattering. In various embodiments,
photosensor regions may be formed from one or more vacuum
photomultipliers, avalanche photodiodes, or silicon
photomultipliers. Each photosensor region, for example, may be
configured as a separate semiconductor in some embodiments, while,
in other embodiments, multiple photosensor regions may be present
on a single semiconductor. In various embodiments, a photosensor
output circuit may be disposed on one or more unit that is separate
from the photosensor regions (e.g., integrated chip (IC) such as
application specific integrated chip (ASIC)). In other embodiments,
at least a portion of a photosensor output circuit may be disposed
on a semiconductor such as a complementary metal oxide
semiconductor (CMOS) on which one or more photosensor regions are
disposed. In some embodiments, a portion of the photosensor output
circuit may be disposed on a CMOS and another portion on an ASIC
(e.g., regional circuits disposed on CMOS and summing circuit
disposed on ASIC).
Returning to FIG. 1, in the illustrated embodiment, the processing
unit 130 is operably coupled separately to the detector unit 105.
The depicted processing unit 130 is configured (e.g., may include
one or more ASIC's and/or FPGA's, and/or includes or is associated
with a tangible and non-transitory memory having stored thereon
instructions configured to direct the processor) to obtain a first
count for at least one signal 108 that corresponds to a first
energy window, with the first energy window corresponding to values
higher than a nominal peak value. For example, for annihilation
photons produced during a PET scan, the photons may have a nominal
peak value of 511 keV. The first energy window may then be placed
higher than the nominal peak value. For example, a minimum energy
for the first energy window may be slightly more than the nominal
peak value. Portions of the signals 108 that correspond to counts
within the first energy window over a predetermined amount of time
may be used to obtain the first count. The processing unit 130 of
illustrated embodiment is also configured to obtain a second count
for at least one signal that corresponds to a second energy window,
with the second energy window corresponding to values lower than a
nominal peak value. Again, for photons produced during a PET scan,
the photons may have a nominal peak value of 511 keV. The second
energy window may then be placed lower than the nominal peak value.
For example, a maximum energy for the second energy window may be
slightly less than the nominal peak value. Portions of the signals
108 that correspond to counts within the second energy window over
a predetermined amount of time may be used to obtain the second
count.
The depicted processing unit 130 is also configured to obtain at
least one auxiliary count for the at least one signal, with the at
least one auxiliary count corresponding to at least one auxiliary
window. In various embodiments, an auxiliary window may be disposed
between energy levels that are lower than the energy levels of the
second window, for example to correspond to portions of a signal
caused by scatter. Alternatively or additionally, an auxiliary
window may be disposed between energy levels that are higher than
the energy levels of the first window, for example to correspond to
portions of a signal caused by pileup. As another example, an
auxiliary window may be disposed between energy levels that are
higher than the energy levels of the first window, for example to
correspond to portions of a signal caused by intrinsics (e.g.,
counts generated by intrinsic radioactivity from within the crystal
array 110, or by radiation from an external source that provides
radiation of known energy for calibration purposes). (For
additional discussion regarding the use of energy windows and the
locations of energy windows, see, for example, FIGS. 4-5 and
related discussion). It may be noted that, in some embodiments,
intrinsic rate may be relatively constant, and intrinsics may be
subtracted out from a signal instead of using an intrinsic window.
In the illustrated embodiment, the processing unit 130 is further
configured to adjust a gain applied to signals based on the first
count, the second count, and the auxiliary count. For example, the
first count, second count, and auxiliary count may be used to track
a peak of the signals. If the peak of the signals differs from the
nominal peak (e.g., 511 keV) or differs from the nominal peak more
than a threshold tolerance level, the gain may be adjusted to bring
the peak to or nearer to the nominal peak value. Thus, if the
determined peak is below (or far enough below) the nominal value,
the gain (e.g., voltage applied to a photosensor region providing
the signals being tracked) may be increased. However, if the
determined peak is above (or far enough above) the nominal value,
the gain may be decreased. If the determined peak is at the nominal
value or within an acceptable range of the nominal value, the gain
may not be adjusted. Accordingly, various embodiments may be
understood as tracking the peak directly, instead of using other
compensation techniques based on indirect measures of peak such as
temperature change, providing improved accuracy. Gain adjustment
may be provided for example by changing the gain of the photosensor
(for example by changing the bias voltage), by changing the gain of
an amplifier (for example, a voltage controlled amplifier or VCA),
or by multiplying a digital representation of the energy by a
factor that represents the gain adjustment (which may be referred
to herein as a virtual gain adjustment). Further, use of one or
more auxiliary windows in various embodiments provides improved
accuracy over using only two windows.
In various embodiments the processing unit 130 includes processing
circuitry configured to perform one or more tasks, functions, or
steps discussed herein. It may be noted that "processing unit" as
used herein is not intended to necessarily be limited to a single
processor or computer. For example, the processing unit 130 may
include multiple processors, ASIC's, FPGA's, and/or computers,
which may be integrated in a common housing or unit, or which may
distributed among various units or housings. It may be noted that
operations performed by the processing unit 130 (e.g., operations
corresponding to process flows or methods discussed herein, or
aspects thereof) may be sufficiently complex that the operations
may not be performed by a human being within a reasonable time
period. For example, the determination of energy values of various
signals and obtaining the counts, as well as tracking the peak
and/or adjusting the gain based on the obtained counts, may rely on
or utilize computations that may not be completed by a person
within a reasonable time period.
In the illustrated embodiment, the processing unit 130 is disposed
onboard the detector unit 105. It may be noted that other types,
numbers, or combinations of modules or portions may be employed in
alternate embodiments, and/or various aspects of modules or
portions described herein may be utilized in connection with
different modules or portions additionally or alternatively.
Generally, the various aspects of the processing unit 130 act
individually or cooperatively with other aspects to perform one or
more aspects of the methods, steps, or processes discussed
herein.
As seen in FIG. 1, the processing unit includes a memory 132. The
memory 132 may include one or more computer readable storage media
(e.g., tangible and non-transitory storage media). The memory 132,
for example, may store information corresponding to the energy
values of one or more signals, count information for the obtained
counts, results of intermediate processing steps, calibration
parameters, or the like. For example, the memory 132 may have
stored thereon one or more formulae or look-up tables that may be
utilized to determine if the obtained counts correspond to a target
or nominal energy peak. Further, the process flows and/or
flowcharts discussed herein (or aspects thereof) may represent one
or more sets of instructions that are stored in the memory 132 for
direction of operations of the PET detection system 100.
It may be noted that, in various embodiments, one or more aspects
of the processing unit 130 may be shared with the detector unit
105, associated with the detector unit 105, and/or disposed onboard
the detector unit 105. For example, in some embodiments, at least a
portion of the processing unit 130 is integrated with the detector
unit 105. In various embodiments, at least a portion of the
processing unit 130 includes at least one application specific
integrated circuit (ASIC) or field programmable gate array (FPGA)
that is disposed onboard or integrated with the detector unit
105.
When obtaining the counts, multiple signals may be joined or
combined to form an evaluation signal from which the counts for the
various windows are obtained. For example, for a photosensor region
that is dedicated to a 3.times.4 sub-array of crystals, there are
12 total elements or blocks of the sub-array. One or more signals
from each of the elements or blocks may be combined with the
signals from other elements or blocks to form a combined signal
which is evaluated to obtain the counts, as far as they show the
same temperature dependence or peak shift trend. FIGS. 3A, 3B, and
3C depict various aspects of combining signals to provide an
evaluation signal in accordance with various embodiments.
For example, FIG. 3A depicts individual signals or histograms 300
(namely 300a, 300b, 300c, 300d, 300e, 300f, 300g, 300h, 300i, 300j,
300k, 300l) corresponding to signals measured responsive to
radiation impacting the crystals of a sub-array. Each individual
histogram 300 is a histogram for a particular crystal of the
sub-array in the measured electrical signal size or ADC bin
(analog-to-digital converted binary). With a total of 12 crystals
in the sub-array for the depicted embodiment, 12 individual
histograms are utilized. The peaks in a histogram represent 511 keV
energy gamma rays even though they are different in ADC bin. The
individual histograms 300 may then be scaled, to provide the scaled
histograms 310 (e.g., scaled to 511 keV) depicted in FIG. 3B. It
may be noted that a difference between the histograms of FIG. 3A
and FIG. 3B is that the former is in a scale of a measured signal
bin (e.g., ADC bin) and the latter is in a scale of a gamma ray
energy bin. For a given 511 keV gamma ray energy deposition, the
peaks may be expected to be the same, but the peaks differ in
practice because of differences in crystal output, optical
coupling, and/or other factors. However, because it is known that
the peak represents 511 keV in the case of annihilation photons, a
gain conversion factor may be calculated so the spectrum may be
re-scaled to be in a keV bin. For example, each crystal may have a
particular value or relationship, determined during a calibration
procedure, that is configured to scale a measured value closer to
an ideal or expected gamma energy value. The particular values or
relationships may be stored as part of a system calibration file.
The scaled histograms 310 of FIG. 3B may then be combined into a
single histogram 320, as seen in FIG. 3C. The various counts for
the windows as discussed herein may be determined using the
combined histogram 320 to determine whether a gain adjustment
should be applied to the sub-array (e.g., to the photosensor region
corresponding to the sub-array). It may be noted that the combined
histogram 320 of the depicted embodiment is not symmetric about the
peak. Instead, for example, a portion 322 corresponding to scatter
may provide a plateau of detected radiation 324 with energies lower
than the peak 326. Because scatter may affect the peak location,
using merely two windows (e.g., an upper and a lower) may not
capture the effect of scatter on the peak. Accordingly, in various
embodiments, three or more windows may be employed to more
accurately track the peak of the energy histogram.
FIG. 4 depicts example windows used in connection with various
embodiments. In the example of FIG. 4, three windows are shown. In
FIG. 4, a histogram 400 (sorted by energy level) is illustrated.
The histogram 400, for example, may be generated as described in
connection with FIG. 3. As seen in FIG. 4, the histogram 400
includes a peak 402 located at about 511 keV. The histogram 400
also includes a portion 404 corresponding to an elevated number of
counts (relative to an ideal, symmetric histogram not affected by
scatter). In the illustrated embodiment, three windows are
depicted: a first window 410 (or upper window), a second window 420
(or lower window), and an auxiliary window 430 (or scatter
window).
The first window 410 has a minimum boundary 412 and a maximum
boundary 414 that are both higher than the nominal peak 402. The
first window 410 accordingly corresponds to values higher than the
nominal peak 402. The second window 420 has a minimum boundary 422
and a maximum boundary 424 that are both lower than the nominal
peak 402. The second window 420 accordingly corresponds to values
lower than the nominal peak 402. The first and second windows are
both positioned to have one boundary (the maximum boundary 424 for
the second window 420 and the minimum boundary 412 for the first
window 410) at or near the nominal peak 402. The auxiliary window
430 has a minimum boundary 432 and a maximum boundary 434 that are
both lower than the nominal peak 402, as well as lower than the
minimum boundary 422 of the second window 420. It may be noted that
in some embodiments, for example, the maximum boundary may not be
lower than the nominal peak 402. In the illustrated embodiment, the
auxiliary window 430 corresponds to energy values corresponding to
or associated with scatter. The particular values that correspond
to or are associated with scatter may vary by application (e.g.,
detector composition or architecture, or radiopharmaceutical(s)
used in connection with PET scan, among others).
As indicated herein, the counts corresponding to the windows 410,
420, 430 may be used to determine whether or not a gain applied to
signals provided by a detector unit is to be adjusted. For example,
the counts may be used to determine a measured peak, and it may be
determined if the measured peak is at or within a tolerable
distance of the nominal peak. If the measured peak is below the
nominal peak, the gain may be increased, or if the measured peak is
above the nominal peak, the gain may be decreased.
In various embodiments, a peak tracking metric may be employed. For
example, for the embodiment depicted in FIG. 4, a peak tracking
metric may be defined as M=U-(L-A*S), where M is the peak tracking
metric, U is the number of counts in the first window 410, L is the
number of counts in the second window 420, S is the number of
counts in the auxiliary window 430, and A is a weighting
coefficient for the auxiliary counts. For example, A may be more
than zero but less than one. It may be noted that A in some
embodiments may be more than one (e.g., for a relatively narrow
window). The higher A is, the more impact the counts in the
auxiliary window 430 have on the metric, while the lower A is, the
less impact the counts in the auxiliary window 430 have on the
metric. In the illustrated embodiment, if M is less than zero, it
is determined that the peak is below the nominal peak and the gain
may be increased, while, if M is greater than zero, it is
determined that the peak is above the nominal peak and the gain may
be increased. In some embodiments, an acceptable or tolerable range
of M may be predetermined, and the gain increased when the value of
M is outside of and below the tolerable range, with the gain
decreased when the value of M is outside of and above the tolerable
range. The particular value of A, as well as the sizes (e.g.,
energy ranges) and locations of the windows may be determined
during a testing or calibration process of a detector unit. For
example, the detector unit may be provided with a known amount of
radiation over varying conditions (e.g., temperature changes and
degree of scatter), and the particular values of A and the window
sizes/locations determined experimentally. The value of M may be
incremented or otherwise updated periodically and maintained on a
running basis. In some embodiments, M may be periodically evaluated
and a counter incremented (or decremented) when M for the most
recent evaluation period is positive (or negative).
The example depicted in FIG. 4 utilizes a single auxiliary window;
however, in other embodiments, two or more auxiliary windows may be
employed. The number, size, and location of auxiliary windows may
vary by application. For example, more windows may be used in
embodiments for which increased accuracy is desired and/or for
which the effects of asymmetry on the histogram more heavily impact
the peak location.
FIG. 5 depicts example windows used in connection with various
embodiments. In the example of FIG. 5, four windows are shown. In
FIG. 5, a histogram 500 (by energy level) is illustrated. The
histogram 500, for example, may be generated as described in
connection with FIG. 3. The example of FIG. 5 may be similar to the
example of FIG. 4 in certain respects. For example, as seen in FIG.
5, the histogram 500 includes a peak 502 located at about 511 keV.
The histogram 500 also includes a portion 504 corresponding to an
elevated number of counts (relative to an ideal, symmetric
histogram not affected by scatter). In the example depicted in FIG.
5, a first window 510 (or upper window), a second window 520 (or
lower window), and an auxiliary window 530 (or scatter window)
generally similar to the windows depicted in FIG. 4 are also shown.
The example of FIG. 5, however, also includes a second auxiliary
window 540. The second auxiliary window 540 is disposed at energies
above the first window 510, and may correspond to energies, for
example, for pile-up and/or other intrinsics (e.g., events
generated by radiation from within a detector unit in contrast to
events from received annihilation photons).
Generally, in various embodiments, the number and location of
auxiliary windows may be selected to address counts attributable to
various causes. As discussed herein, for example, counts
attributable to scatter may affect the symmetry of the histogram
and the peak location. As another example, counts attributable to
intrinsic radiation (e.g., events from a crystal array or other
scintillator itself) may affect the symmetry of the histogram and
the peak location. As another example, counts attributable to
pile-up may affect the symmetry of the histogram and peak location.
Counts attributable to pile-up may increase with count rate.
Accordingly, the weight of a variable associated with a pile-up
window (and/or other windows) may be adjusted based on count rate.
As one more example, counts related to dirty isotopes may affect
the symmetry of the histogram and peak location. Accordingly, in
some embodiments, the processing unit 130 may be configured to vary
values for the weights used to determine a peak tracking metric
based on type of radiopharmaceutical administered to an object to
be imaged. For example, an auxiliary window corresponding to energy
values for dirty isotopes may be employed for a first
radiopharmaceutical, but the auxiliary window for dirty isotopes
may not be employed when a second radiopharmaceutical that is free
of extraneous energy peaks is utilized. Alternatively, the pile-up
window may be used for a pharmaceutical that is free of extraneous
energy peaks, but not for an isotope such as I-124 which has a
strong emission at 602 keV.
Similar to the example of FIG. 4, the first window 510 has a
minimum boundary 512 and a maximum boundary 514 that are both
higher than the nominal peak 502. Also, the second window 520 has a
minimum boundary 522 and a maximum boundary 524 that are both lower
than the nominal peak 502. As with the example of FIG. 4, the first
and second windows are both positioned to have one boundary (the
maximum boundary 524 for the second window 520 and the minimum
boundary 512 for the first window 510) at or near the nominal peak
502.
In the example depicted in FIG. 5, however, two auxiliary windows
are used, namely, a first auxiliary window 530 and a second
auxiliary window 540. The first auxiliary window 530 may be
generally similar to the first auxiliary window 430 in respects.
For example, the auxiliary window 530 has a minimum boundary 532
and a maximum boundary 534 that are both lower than the nominal
peak 502, as well as lower than the minimum boundary 522 of the
second window 520. In the illustrated embodiment, the first
auxiliary window 530 corresponds to energy values corresponding to
or associated with scatter.
As seen in FIG. 5, the second auxiliary window 540 has a minimum
boundary 542 and a maximum boundary 544 that are both higher than
the nominal peak 502, as well as higher than the maximum boundary
514 of the first window 510. In the illustrated embodiment, the
second auxiliary window 540 corresponds to energy values
corresponding to or associated with intrinsic radiation.
Additionally or alternatively, the second auxiliary window 540 in
various embodiments may correspond to energy values corresponding
to or associated with pile-up. In the illustrated embodiment, the
windows do not overlap. It may be noted that, in some embodiments,
windows may overlap.
As with the example discussed in connection with FIG. 4, a peak
tracking metric may be employed for the example discussed in FIG.
5. For example, for the embodiment depicted in FIG. 5, a peak
tracking metric may be defined as M=U-L-A*(A1+A2)-B*(A1-A2), where
M is the peak tracking metric, U is the number of counts in the
first window 510, L is the number of counts in the second window
520, A1 is the number of counts in the first auxiliary window 530,
A2 is the number of counts in the second auxiliary window 540, and
A and B are weighting coefficients for the auxiliary counts. It may
be noted that in some embodiments a running total for a peak
tracking metric may be maintained, with the running total used to
determine adjustments to the gain. In some embodiments, a peak
tracking metric based on the total counts for each window over a
predetermined time interval may be sampled and used to periodically
adjust the gain at predetermined intervals. It may be noted that,
in some embodiments, a running accumulator may be updated with
weighted new events, with each event being weighted individually
right when it happens (based on the corresponding window) and added
to the running accumulator.
Additional and/or alternative windows, weighting factors, and/or
metrics may be employed in various embodiments. Generally, in
various embodiments, a peak tracking metric may be employed that
uses corresponding weights for a given number of windows (e.g., a
first window for values in a range above a nominal peak, a second
window for values in a range below the nominal peak, and one or
more auxiliary windows). The peak tracking metric may be determined
by applying at least one corresponding weight to at least one of
the first count, the second count, and at least one auxiliary
count. In various embodiments, the weights may only be used to
modify the count values for auxiliary windows. Next, it may be
determined if the peak tracking metric is within a predetermined
range corresponding to the nominal peak for a given number of
received counts. In some embodiments, a metric value of zero
corresponds to the peak being at the value of the nominal peak, a
positive value indicates a peak above the nominal value, and a
negative value indicated a peak below the nominal value. In various
embodiments, a peak tracking metric may be maintained on a running
basis and incremented or decremented based on counts received, with
the gain adjusted when the running total exceeds a threshold. In
various embodiments, the gain may be increased if the peak tracking
metric is lower than the predetermined range, or decreased if the
peak tracking metric is higher than the predetermined range. It may
be noted that alternative or additional techniques may be employed
to determine a peak location and/or a peak tracking metric. For
example, in some embodiments, intrinsics, if known, may be
subtracted out when preparing a histogram from which to obtain
window counts. For example, with a nominal peak value of 511 keV,
all readings above 700 keV may be subtracted out in some
embodiments. As another example, in some embodiments, a value for
the peak may be determined and compared directly to a nominal or
desired peak value in order to determine whether a gain is to be
adjusted, and if so, by how much.
As noted herein, the gain associated with a particular photosensor
portion or region (as well as corresponding crystal element or
group of elements such as a sub-array), may be adjusted. For
example, in some embodiments, the gain may be adjusted (e.g., under
the control of the processing unit 130) by varying a voltage
applied to the detector unit 105. The voltage may be varied by a
predetermined step, irrespective of the distance from the
predetermined range or target for a peak tracking metric. For
example, as long as the metric is below the predetermined range, a
predetermined positive step may be added to the voltage in some
embodiments. In some embodiments, the processing unit 130 may be
configured to repeat a gain adjustment in a predetermined time
interval, for example by resetting counters. As discussed herein,
in some embodiments, the voltages corresponding to different
sub-arrays may be adjusted independent of each other. For example,
in the embodiment depicted in FIG. 1, a voltage V1 applied to the
first photosensor region 121 may be adjusted independently of a
voltage V2 applied to the second photosensor region 122. It may be
noted that, alternatively or additionally, the voltage may be
varied by an amount that estimates a magnitude of the peak shift,
for example, by considering both the metric and the total counts
observed by the windows. Varying the voltage by a predetermined
step may improve stability of adjustment, while varying the voltage
by an amount that considers the magnitude of the peak shift may
improve the quickness of response.
FIG. 6 provides a flowchart of a method 600 (e.g., for tracking an
energy peak and/or adjusting a gain of a detection system) in
accordance with various embodiments. The detection system, for
example, may be configured for use with a PET imaging system. The
method 600, for example, may employ, include, or relate to
structures or aspects of various embodiments discussed herein. In
various embodiments, certain steps may be omitted or added, certain
steps may be combined, certain steps may be performed
simultaneously, certain steps may be performed concurrently,
certain steps may be split into multiple steps, certain steps may
be performed in a different order, or certain steps or series of
steps may be re-performed in an iterative fashion. In various
embodiments, portions, aspects, and/or variations of the method 600
may be used as one or more algorithms (e.g., software modules or
other instructions stored on a tangible and non-transitory computer
readable medium utilizing or based on the one or more algorithms)
to direct hardware (e.g., processing unit 130 or portion thereof)
to perform one or more operations described herein.
At 602, an object to be imaged is positioned within the field of
view of a PET imaging system. The object, for example, may be a
human patient that has been administered a radiopharmaceutical.
At 604, radiation events are received by at least one detector unit
of the PET imaging system. The radiation events, for example, may
be events caused by annihilation events within the human patient.
Radiation from the patient may impact a crystal array of the at
least one detector unit, which then emits light photons to one or
more photosensors responsive to the radiation impact.
At 606, signals responsive to radiation events impacting the
detector unit are generated. For example, photosensors receiving
light photons may provide an electrical signal as an output
responsive to reception of the light photons. A gain may be applied
to the signals to calibrate the signals to a known or expected
energy level of the radiation received from the object being
imaged. Because the behavior of the detector unit or portions
thereof may vary over time (e.g., due to temperature change), for
accurate measurement, determination, and identification of
radiation events the gain may be adjusted as discussed herein. As
discussed herein, multiple signals (e.g., signals associated with
individual blocks or units of a sub-array of a crystal array) may
be combined (e.g., scaled and combined) to form a combined signal
which is used to obtain counts for multiple windows. For example,
signals corresponding to individual elements of the sub-array may
be independently scaled based on a predetermined calibration. The
signal may be represented as a histogram sorted by energy level in
various embodiments.
At 608, a first count for at least one of the signals generated at
606 is obtained. The first count is for a first energy window
corresponding to values higher than a nominal or target peak value
(e.g., 511 keV). The first count may be obtained by adding the
number of total counts from a histogram sorted by energy level that
fall between upper and lower boundaries of the first energy
window.
At 610, a second count for the at least one of the signals
generated at 606 is obtained. The second count is for a second
energy window corresponding to values lower than a nominal or
target peak value (e.g., 511 keV). The second count may be obtained
by adding the number of total counts from a histogram sorted by
energy level that fall between upper and lower boundaries of the
second energy window. In the case of a symmetric histogram centered
about the peak, the first and second count windows may reliably and
accurately be used to track the location of a peak relative to the
nominal peak. However, in practice, the histograms generated during
PET detection may not be symmetric, for example due to scatter or
intrinsic radiation events, among others. Accordingly, as discussed
herein, auxiliary windows may be used to address or account for
asymmetries in an energy histogram to improve the accuracy and
reliability of energy peak determination and/or tracking.
At 612, at least one auxiliary count for at least one of the
signals generated at 606 is obtained. Each auxiliary count is for a
corresponding auxiliary energy window. Auxiliary energy windows may
be disposed below and/or above the nominal peak value. In some
embodiments, a scatter window corresponding to scatter energy
values may be used as an auxiliary energy window. Alternatively or
additionally, an intrinsic window corresponding to intrinsic
radiation energy values for the detector unit (or portions thereof
such as a crystal array) may be used as an auxiliary window.
At 614, a gain applied to signals generated by the detector unit is
adjusted based on the first count, the second count, and the at
least one auxiliary count. For example, a peak tracking metric may
be determined using the window counts. A weight may be applied to
at least one of the window counts. For example, a weight may be
applied to the at least one auxiliary count to determine the peak
tracking metric. In some embodiments, it may then be determined if
the peak tracking metric is within a predetermined range. For
example, in some embodiments a peak tracking metric of zero may
correspond to the peak value being at the nominal peak value, and
it may be determined if the absolute value of the peak tracking
metric exceeds a threshold. If the peak tracking metric is outside
of the predetermined range, the gain may be adjusted (e.g.,
increased if the peak tracking metric is below the predetermined
range, and decreased if the peak tracking metric is above the
predetermined range. It may be noted that particular relationships
between the counts used to obtain the peak tracking metric may be
determined during a calibration of the detector unit (or during a
calibration of a representative detector unit). In various
embodiments, counts may be sampled over collection periods, with
the peak tracking metric calculated for each collection period, and
a running total of the peak tracking metric updated after each
collection period. The running total of the peak tracking metric
may be used to determine appropriate gain adjustment.
In some embodiments, the gain may be adjusted by varying a voltage.
For example, at 616 of the illustrated embodiment, the voltage
applied to at least one detector unit (e.g., a photosensor region
of the detector unit) is varied. For example, the voltage may be
varied by a predetermined step (e.g., a predetermined step increase
applied if the peak is below a target range, or a predetermined
step decrease applied if the peak is above the target range). It
may be noted that, as discussed herein, gain may be adjusted other
than by applying a voltage to the detector (e.g., by adjusting a
gain of an amplifier, or by multiplying a digital representation of
a received energy by a gain factor). It may be noted that other
considerations may be accounted for in addition to the location of
a peak tracking metric being outside a target range. For example, a
conventional temperature based adjustment may be made additionally,
with the conventional temperate based adjustment given priority
over the peak tracking metric. Alternatively, the peak tracking
metric may be given priority over the conventional temperature
based adjustment. Further, limits may be placed on a number of gain
adjustments made within a given amount of time, or frequency of
gain adjustments. As another example, a series of signals may be
obtained and analyzed, with the gain adjusted only if the series
satisfies one or more predetermined criteria (e.g., a total amount
of peak drift, a rate of peak drift, or the like). More recently
obtained signals may be given a higher weighting than previously
obtained signals in determining if the series of signals satisfies
the predetermined criteria.
FIGS. 7-9 illustrate a PET imaging system with which various
embodiments described herein may be employed. In other embodiments,
crystal arrays as discussed herein may be utilized with other
imaging systems (e.g., imaging systems configured for one or more
additional or alternative modalities). FIG. 7 illustrates a PET
scanning system 1 including a gantry 10 that supports a detector
ring assembly 11 about a central opening or bore 12. The detector
ring assembly 11 in the illustrated embodiments is generally
circular and is made up of plural rings of detectors spaced along a
central axis 2 to from a cylindrical detector ring assembly. In
various embodiments, the detector ring assembly 11 may include 5
rings of detectors spaced along the central axis 2. A patient table
13 is positioned in front of the gantry 10 and is aligned with the
central axis 2 of the detector ring assembly 11. A patient table
controller (not shown) moves the table bed 14 into the bore 12 in
response to commands received from an operator work station 15
through a communications link 16. A gantry controller 17 is mounted
within the gantry 10 and is responsive to commands received from
the operator work station 15 through a second communication link 18
to operate the gantry.
As shown in FIG. 8, the operator work station 15 includes a central
processing unit (CPU) 50, a display 51, and a keyboard 52. An
operator may use the keyboard to control the calibration of the PET
scanner, the configuration of the PET scanner, and the positioning
of the patient table for a scan. Also, the operator may control the
display of the resulting image on the display 51 and/or perform
image enhancement functions using programs executed by the work
station CPU 50.
The detector ring assembly 11 includes a number of detector
modules. For example, the detector ring assembly 11 may include 36
detector modules, with each detector module including eight
detector blocks. An example of one detector block 20 is shown in
FIG. 7. The detector blocks 20 in a detector module may be
arranged, for example, in a 2.times.4 configuration such that the
circumference of the detector ring assembly 11 is 72 blocks around,
and the width of the detector assembly 11 is 4 detector blocks
wide. Each detector block 20 may include a number of individual
detector crystals. In the illustrated embodiment, the array of
detector crystals 21 is situated in front of four photosensors 22.
The photosensors 22 are depicted schematically as photomultiplier
tubes; however, it may be noted that SiPM's may be employed in
various embodiments. Other configurations, sized and numbers of
detector crystals, photosensors and detector modules may be
employed in various embodiments.
During a PET scan, an annihilation photon may impact one of the
detector crystals 21. The detector crystal 21, which may be formed,
for example of lutetium yttrium silicate (LYSO) or bismuth
germinate (BGO), converts the annihilation photon into a number of
photons which are received and detected by the photosensors. The
photons generated by a detector crystal generally spread out to a
certain extent and travel into adjacent detector crystals such that
each of the four photosensors 22 receives a certain number photons
as a result of an annihilation photon impacting a single detector
crystal 21.
In response to a scintillation event, each photosensor 22 produces
a signal 23A-23D on one of the lines A-D, as shown in FIG. 9, which
rises sharply when a scintillation event occurs and then tails off
exponentially. The relative magnitudes of the signals are
determined by the position in the detector crystal array at which
the scintillation event took place. The energy of the annihilation
photon which caused the scintillation event determines the total
magnitude of the four signals. The time that the signal begins to
rise is determined by when the scintillation event occurs and the
time required for photons to travel from the position of the
scintillation event to the photosensors. The example depicted in
FIG. 9 provides an example based on a vacuum photodetector;
however, it may be noted that certain principles disclosed herein
may also be applied to SiPM detectors generally.
As shown in FIG. 8, a set of acquisition circuits 25 is mounted
within the gantry 10 to receive the four signals from the detector
block 20. The acquisition circuits 25 determine timing, energy and
the event coordinates within the array of detector crystals using
the relative signal strengths. The results are digitized and sent
through a cable 26 to an event locator circuit 27 housed in a
separate cabinet 28. Each acquisition circuit 25 also produces an
event detection pulse which indicates the exact moment the
scintillation event took place.
The event locator circuits 27 form part of a data acquisition
processor 30 which periodically samples the signals produced by the
acquisition circuits 25. The data acquisition processor 30 has an
acquisition CPU 29 which controls communications on the local area
network 18 and a bus 31. The event locator circuits 27 assemble the
information regarding each valid event into a set of digital
numbers that indicated when the event took place and the identity
of the detector crystal 21 which detected the event. The event
locator circuits 27, for example, may use a detector position map
to map a pair of coordinates to the detector 21 which detected the
event.
The event data packets are transmitted to a coincidence detector 32
which is also part of the data acquisition processor 30. The
coincidence detector 32 accepts the event data packets from the
event locator circuits 27 and determines if any two of them are in
coincidence. Coincidence is determined by a number of factors. For
example, time markers in each event data packet may be required to
be within a specified time period of each other, e.g., 4.57 ns. As
another example, the locations indicated by the two event data
packets may be required to lie on a straight line which passes
through the field of view (FOV) of the scanner bore 12. Events
which cannot be paired are discarded, but coincident event pairs
are located and recorded as a coincidence data packet that is
transmitted through a serial link 33 to a sorter 34. The format of
the coincidence data packet may be, for example, a 48 bit data
stream which includes, among other things, a pair of digital
numbers that precisely identify the locations of the two detector
crystals 21 that detected the event and the time difference between
them.
The sorter 34, which may include a CPU and which forms part of an
image reconstruction processor 40, receives the coincidence data
packets from the coincidence detector 32. The function of the
sorter 34 is to receive the coincidence data packets and allocate
sinogram memory for the storage of the coincidence data. The set of
all projection rays that point in the same direction (A) and pass
through the scanner's field of view is a complete projection, or
"view", a set of which makes a sinogram. The distance (R) between a
particular projection ray and the center of the field of view
locates that projection ray within the view. As shown in FIG. 6,
for example, an event 50' occurs along a projection ray 51' which
is located in a view at the projection angle .theta. and the
distance R. The sorter 34 counts all of the events that occur on
this projection ray (R, .theta.) during the scan by sorting out the
coincidence data packets that indicate an event at the detector
crystals 21 lying on the projection ray. During an emission scan,
the coincidence counts are organized in memory 43, for example as a
set of two-dimensional array, one for each axial image, and each
having as one of its dimensions the projection angle .theta. and
the other dimension the distance R. This .theta. by R map of the
measured events may be referred to as sinogram array 48. The sorter
34 may also organize the coincidence events into other data
formats. In a projection plane format, for example, other variables
may be used to define coincidence events which are detected by
pairs of detector crystals 21 in non-adjacent detector rings.
Coincidence events occur at random and the sorter 34 determines the
.theta. and R values from the two crystal addresses in each
coincidence data packet and increments the count of the
corresponding sonogram array element. At the completion of the
emission scan, the sinogram array 48 stores the total number of
annihilation events which occurred along each ray. The array
processor 45 reconstructs an image from the data in the sinogram
array 48. First, however, a number of corrections may be made to
the acquired data to correct for measurement errors such as those
caused by attenuation of annihilation photons by the patient,
detector gain non-uniformities, random coincidences, and integrator
dead time. Each row of the corrected sinogram array is then Fourier
transformed by the array processor 45 and multiplied by a
one-dimensional filter array. The filtered data is then inverse
Fourier transformed, and each array element is back projected to
form the image array 46. The image CPU 42 may either store the
image array data or output the data to the operator work station
15.
Certain previous embodiments discussed herein employ windows
associated with a peak energy of received radiation. It may be
noted that various embodiments may alternatively or additionally
use windows disposed at other portions of a spectrum of energy
detected by a detector. For example, various embodiments may employ
a number of windows disposed at various points of the spectrum to
provide gain adjustment based on a spectral shape or spectral
signature. Such windows may or may not be associated with received
energy. For example, in some embodiments, two or more windows may
be disposed about a peak of intrinsic energy (e.g., radiation
generated from within a detector, in distinction from radiation
received by the detector from an outside source such as a human
patient or other object being imaged).
For example, in some embodiments, the processing unit 130 may be
configured to obtain, during an imaging process, a first count for
at least one signal corresponding to a first intrinsic energy
window and to obtain, during the imaging process, a second count
for the at least one signal corresponding to a second intrinsic
energy window. An imaging process as used herein may be understood
as a process during which information for generating an image to be
reconstructed is obtained. For the purposes of clarity and
avoidance of doubt, an imaging process as used herein does not
include use of a detector during a process in which no object to be
imaged is analyzed. For example, a calibration process (e.g., a
calibration process performed overnight or during another period
when the detector is not being used for imaging) that is performed
independent of imaging an object is not an imaging process as used
herein. It may be noted that additional counts for additional
windows may also be obtained and utilized in various embodiments.
The first intrinsic energy window corresponds to values higher than
an intrinsic peak value, and the second intrinsic energy window
corresponds to values lower than the intrinsic peak value. The
intrinsic peak, and associated counts, may be due to an intrinsic
source within a detector unit (e.g., detector unit 105) such as
Lutetium (e.g., Lu-176). It may be noted that other windows (e.g.,
windows associated with a different intrinsic peak and/or more than
two windows associated with an intrinsic peak) may be used
additionally or alternatively in various embodiments. The
processing unit 130 in various embodiments adjusts a gain applied
to signals (e.g., received and/or intrinsic signals) based on the
first count and the second count. For example, a weighted sum may
be used using the first count and the second count (and, in various
embodiments, additional counts from additional windows), with the
counts from each window being multiplied by a predetermined
weighting factor before adding the counts for the weighted sum. For
computing the weighted sum, counts for the particular windows may
be accumulated for a given time period (e.g., one second), and the
weighted sum re-calculated for the given time period.
Alternatively, the weighted sum may be computed on an ongoing
basis; in this case, each window has an associated weight, and when
an event is determined to fall within a certain window, the
corresponding weight is added to the running sum. Based on the
value of the weighted sum, the gain is adjusted. For example, if
the weighted sum is higher than a target value, the gain may be
decreased, and if the weighted sum is lower than a target value,
the gain may be increased. In the case of a running sum, the target
value can be adjusted continuously, based on the number of counts
received. For example, because of the random nature of the arrival
of events of different energy, the weighted sum will slowly diverge
from zero in a manner that follows a Gaussian random walk, where
the expected deviation scales with the square root of the number of
steps taken (or number of events detected). A criterion for
adjusting gain may then be computed by evaluating the inequality
S*S>f*N Where S is the running sum, N is the total number of
events, and f is some predetermined scale factor, for example 5.
When the factor f is large, only large gain errors will result in
an adjustment; when it is small, a small deviation will result in
an adjustment. In order to improve stability of the algorithm, the
accumulator N may be initialized to a value greater than zero (for
example 200) when event accumulation begins; this will ensure that
several hundred events will have to be detected before a gain
adjustment is made.
It may be noted that the gain may be adjusted by adjusting a
voltage supplied to the detector unit 105. Additionally, or
alternatively, the gain may be adjusted virtually by adjusting
measured values received from the detector unit. For example, if a
3% increase in gain is determined for the adjustment, received
measured values may be multiplied by 1.03 to provide adjusted
values for farther processing (e.g., use for image
reconstruction).
In various embodiments, windows associated with intrinsic radiation
as well as windows associated with received radiation may be
utilized in determining a gain adjustment. For example, the
processing unit 130 may be configured to (in addition to obtaining
the first and second counts for the first and second intrinsic
windows corresponding to an intrinsic portion of as signal) obtain
counts corresponding to windows associated with a received energy
peak (e.g., energy received due to radiation received from a
patient being imaged having a nominal peak value for a known
isotope) for at least one signal, and adjusting the gain based on
the first count, the second count, and the counts for windows
associated with the received energy peak. The particular number of
windows, and weighting factors applied to the counts for the
windows, may be tailored to suit the desired performance for a
given embodiment. The weighting factors may be selected, for
example, based on an anticipated or expected shape of an energy
spectrum for a given detector, administered radiopharmaceutical,
and/or imaging procedure.
It may be noted that windows associated with intrinsic radiation
may be useful in providing improved accuracy or robustness of
signal analysis for gain determination when radiation is received
from an object to be imaged, as well as provide for gain adjustment
and/or calibration when radiation is not received from an object to
be imaged. For example, in some embodiments, the gain may be
adjusted (e.g., by the processing unit 130) using the first count
and the second count for counts otherwise associated with intrinsic
radiation) during an initial start-up period (e.g., a period in
which a patient is not within the bore of a detector and/or has not
yet been administered a radiopharmaceutical, or during which the
detector is otherwise not receiving radiation from an object to be
imaged). Then, when a patient or other object is disposed within
the bore, and the detector receives radiation from an external
source (e.g., the patient or other object), the gain is adjusted
using the first count and the second, as well as counts for windows
associated with a received energy peak or portion of a signal).
FIG. 10 depicts an energy spectrum with example windows in
accordance with various embodiments. The energy spectrum is plotted
as a signal 1000 with a total number of counts of events (e.g.,
counts over a predetermined time period) along the vertical axis
and energy of the events along the horizontal axis. As seen in FIG.
10, a signal 1000 includes a first intrinsic portion 1010 including
a first intrinsic peak 1012 and a received radiation portion 1020
including a received radiation peak 1022. (It may be noted that
different and/or additional peaks or portions may be present in
other embodiments, for example, depending on detector material
and/or radiopharmaceutical administered to a patient being imaged).
For the example depicted in FIG. 10, the first intrinsic peak 1012
is at a nominal 307 keV (for Lu-176) and the received radiation
peak 1022 is shown at a nominal 511 keV. It may be noted that a
second intrinsic portion 1030 including a second intrinsic peak
1032 may be seen in the illustrated embodiment at a nominal 202
keV. Further, a third intrinsic portion 1040 is also shown in FIG.
10. It may be noted that the first intrinsic portion 1010 and the
second intrinsic portion 1030 are at relatively lower energies with
respect to the received radiation portion 1020, and the third
intrinsic portion 1040 is at a relatively higher energy with
respect to the received radiation portion 1020. It may be noted
that the intrinsic portions correspond to radiation from within a
detector (e.g., from within a crystal of the detector) or from a
source that is not being imaged (e.g., a calibration source),
whereas the received radiation portion corresponds to radiation
received from an object being imaged.
For the embodiment depicted in FIG. 10, there are four windows
associated with the first intrinsic portion 1010 of the signal
1000. A first intrinsic window 1013 and a second intrinsic window
1014 may be referred to as inner windows as they are more centrally
located with respect to the first intrinsic peak 1012, and a third
intrinsic window 1015 and fourth intrinsic window 1016 may be
referred to as outer windows as they are more externally located
with respect to the first intrinsic peak 1012 than the first
intrinsic window 1013 and the second intrinsic window 1014.
An additional four windows are associated with the received
radiation portion 1020 for the embodiment depicted in FIG. 10. A
first received radiation window 1023 and a second received
radiation window 1024 may be referred to as inner windows as they
are more centrally located with respect to the received radiation
peak 1022, and a third received radiation window 1025 and fourth
received radiation window 1026 may be referred to as outer windows
as they are more externally located with respect to the received
radiation peak 1022 than the first received radiation window 1023
and the second received radiation window 1024.
The counts from each window are assigned a weight, with the counts
from each window multiplied by the corresponding weight to provide
a weighted count for each window. Then, the weighted count for all
windows may be added to provide a weighted sum. Based on the
weighted sum, the gain may be adjusted. For example, if the
weighted sum is below a predetermined threshold (e.g., zero), the
gain may be increased, and if the weighted sum is above a
predetermined threshold (e.g., zero), the gain may be decreased.
The particular values of weightings, number of windows, location of
windows, size of windows, and thresholds employed for increasing or
decreasing the gain may be varied to suit a given application, and
may be determined and/or adjusted as part of a calibration process
for a particular imaging system. It may be noted that the total
number of windows used may be scaleable to be tuned to expected
radiation levels for a given application.
The table below lists example weightings for the windows of FIG. 10
associated with the first intrinsic portion 1010 and received
radiation portion 1020. It may be noted that the values in the
table are provided by way of example and that other values may be
employed in various embodiments.
TABLE-US-00001 Lower Upper Corresponding Boundary Boundary
Weighting Window Signal Portion (keV) (keV) Coefficient Third
intrinsic First intrinsic 257 277 0.15 window 1015 portion 1010
First intrinsic First intrinsic 277 307 -(0.40) window 1014 portion
1010 Second intrinsic First intrinsic 307 337 0.40 window 1014
portion 1010 Fourth intrinsic First intrinsic 337 357 -(0.15)
window 1016 portion 1010 Third received Received 461 481 0.55
radiation radiation window 1025 portion 1020 First received
Received 481 511 -(1.0) radiation radiation window 1023 portion
1020 Second received Received 511 541 1.0 radiation radiation
window 1024 portion 1020 Fourth received Received 541 561 -(0.55)
radiation radiation window 1026 portion 1020
As discussed herein, a weighted sum may be generated using the
number of counts and the weighting coefficients. This may be
expressed as
S=(w.sub.1*c.sub.1)+(w.sub.2*c.sub.2)+(w.sub.3*c.sub.3)+ . . . ,
where S is the weighted sum, w.sub.n is the count for the n.sup.th
window, and c.sub.n is the weighting coefficient for the n.sup.th
window. This may also be expressed as
S=.SIGMA..sub.i=1.sup.nw.sub.ic.sub.i where n corresponds to the
number of windows. It may be noted that the inner windows are more
heavily weighted than the outer windows, and that the sign of the
weighting factors alternates in the illustrated embodiment.
Accordingly, events nearer the nominal peak tend to be weighted
more heavily than events farther from the nominal peak. Also,
events associated with received radiation tend to be weighted more
heavily than events associated with intrinsic radiation (e.g., to
allow for use of events associated with intrinsic radiation while
still more heavily weighting received radiation to account for
scatter leakage). The use of four windows in various embodiments
provides a robust metric. For example, for a given received
radiation peak, four windows may be sufficient to estimate the
result of combined received radiation (e.g., the degree to which a
peak differs from a nominal center such as 511 keV), scatter, and
an intrinsic background. It may also be noted that, in the depicted
example, the sign of the weighting coefficients alternates between
adjacent windows. In various embodiments, use of such alternating
positive and negative weighting coefficients with four or more
windows about a peak may help account for a non-zero average slope
of the signal in the area around the peak. For example, for an
intrinsic peak, a relatively large amount of downscatter may occur
as count rate increases. Weighting coefficients may be selected to
help ensure that the downscatter does not result in a bias in the
position of the peak. In some embodiments, the weighting
coefficient associated with the intrinsic portion of the signal may
be selected based on an assumption that the intrinsic peak is
comprised of a symmetrical Gaussian shape imposed on top of a
linear slope.
It may be noted that additional or alternative windows may be used
in various embodiments, for example to fine tune the results in the
case of high count rates (e.g., peak distortion due to pileup)
and/or to correct for spillover from higher peaks (e.g., "dirty"
radiotracers). For example, as seen in FIG. 10, an auxiliary window
1050 is disposed to the right of (or at a higher energy than) the
received radiation portion 1020 to provide a total of 9 windows. In
the illustrated embodiment, the auxiliary window 1050 is associated
with the third intrinsic portion 1040 and is used to accumulate or
count events associated with the third intrinsic portion 1040. In
various embodiments, an additional or alternative auxiliary window
may be employed to help account for "dirty" isotopes that may
change the shape of the spectrum.
It may further be noted that, in an example scenario where the
initial peak position of a given portion of a spectrum is too far
removed from a nominal or expected correction (e.g., due to drift),
the use of alternating signs between inner and outer windows may
provide the resulted weighted sum with the wrong sign (e.g., in
embodiments where a value above zero corresponds to a gain
adjustment in one direction and a value below zero corresponds to a
gain adjustment in an opposite direction), resulting in an
inappropriate adjustment of gain in an incorrect direction. In
various embodiments, if the peak is determined to not be
appropriately centered on four (or more) associated windows, a
different weighting scheme, or coarse adjustment scheme, may be
used to estimate the direction of the correction; while if the peak
is determined to appropriately centered, a fine adjustment
weighting scheme (e.g., using weighting coefficients from the table
above, with alternating signs) may be employed. In some
embodiments, the coarse adjustment scheme may use the same windows
as the fine adjustment scheme, but with different weighting
coefficients. For example, the weighting coefficients for the first
intrinsic window 1013 and third intrinsic window 1015 for a coarse
adjustment scheme may be negative, and the weighting coefficients
for the second intrinsic window 1014 and fourth intrinsic window
1015 for a coarse adjustment scheme may be positive (and/or the
weighting coefficients for the first received radiation window 1023
and third received radiation window 1025 may be negative, and the
weighting coefficients for the second received radiation window
1024 and fourth window 1025 may be positive), with the gain
increased for a negative resulting weighted sum or decreased for a
positive resulting weighted sum. In other embodiments, different
windows may be employed for the coarse adjustment relative to the
fine adjustment.
In various embodiments, the processing unit 130 may be configured
to select an adjustment technique (e.g., fine adjustment or coarse
adjustment) based on a peak analysis metric, which may be computed
by the processing unit 130. The peak analysis metric in various
embodiments is based on a weighted sum of windows around a given
peak. The peak analysis metric in various embodiments provides an
indication that there are more counts in the inner windows relative
to the outer windows (e.g., that the peak is relatively centered
about the four windows). For example, depending on their relative
widths, the outer windows may receive a weighting coefficient of
-(1.0) and the inner windows may receive a weighting coefficient of
1.0. The peak analysis metric is then computed using one or more
weighted sums. For example, the peak analysis metric may be
computed using
P=(.SIGMA.(w.sub.i*x.sub.i))/(.SIGMA.(|w.sub.i|*x.sub.i)), where P
is the peak analysis metric, w.sub.i is the weighting coefficient
for a given window and xi is the number of counts for the given
window. A positive result for P indicates more counts in the inner
windows (e.g., the peak is centered and the fine adjustment scheme
used), and a negative result indicating more counts in the outer
windows (e.g., the peak is not centered and the coarse adjustment
scheme used). In some embodiments, a value of P as 0.25 may be
employed as a threshold, with the signal considered on peak when P
is above 0.25. It may be noted that other metrics and/or other
thresholds may be used in alternate embodiments for determining
which adjustment technique to employ. In some embodiments, when it
is determined that the gain determined by the fine adjustment
technique is in an inappropriate direction, the processing unit 130
may automatically adjust the gain in the opposite direction to that
determined. Such an adjustment in the opposite direction may be in
a smaller increment than called for by the original
determination.
In some embodiments, a running count of 3 accumulators (or weighted
sums) may be kept--a first weighted sum for a fine adjustment
technique, a second weighted sum for a coarse adjustment technique,
and a peaking weighted sum for determining which of the fine
adjustment technique or coarse adjustment technique to use.
In some embodiments, for example to help prevent changes in gain
from occurring too rapidly, the statistical significance of an
accumulated signal (and/or associated counts) may be determined.
Then, depending on the significance of a gain adjustment metric or
calculation, it may be determined whether or not to adjust the
gain. Accordingly, in various embodiments, the processing unit 130
is configured to determine a stability metric, and to determine
whether or not to adjust the gain based on the stability metric. By
comparing the evolution of such a metric over time when the
spectrum is on-peak compared to when the spectrum was off-peak in
various embodiments, it was found that the metric may grow in
proportion with the square root of the number of counts, and that,
for a peak shift, the metric may grow linearly. Accordingly, with
appropriately selected coefficients A and B, the following
inequality may be employed as a stability metric: (acc)^2>A*N+B,
where acc is an accumulated count (e.g., a weighted sum) for a
given accumulation period and N is a number of accumulation periods
(e.g., number of accumulation periods since a gain adjustment).
However, it may be noted that a shift in counts that is significant
may be masked by a sufficiently high number of accumulation periods
N. Accordingly, a very small gain adjustment and re-setting of N to
zero may be periodically performed. For example, if a number of
counts or periods occurs without any gain adjustment, a small gain
adjustment (e.g., a smaller adjustment than made for adjustments
called for by a spectral analysis of the signal) may be made (e.g.,
an adjustment of 0.1%).
FIG. 11 provides a flowchart of a method 1100 (e.g., for tracking
an energy peak and/or adjusting a gain of a detection system) in
accordance with various embodiments. The detection system, for
example, may be configured for use with a PET imaging system. The
method 1100, for example, may employ, include, or relate to
structures or aspects of various embodiments discussed herein. In
various embodiments, certain steps may be omitted or added, certain
steps may be combined, certain steps may be performed
simultaneously, certain steps may be performed concurrently,
certain steps may be split into multiple steps, certain steps may
be performed in a different order, or certain steps or series of
steps may be re-performed in an iterative fashion. In various
embodiments, portions, aspects, and/or variations of the method
1100 may be used as one or more algorithms (e.g., software modules
or other instructions stored on a tangible and non-transitory
computer readable medium utilizing or based on the one or more
algorithms) to direct hardware (e.g., processing unit 130 or
portion thereof) to perform one or more operations described
herein.
At 1102, signals are generated with a detector unit. The signals
may include intrinsic events (caused by radiation within the
detector) and/or received radiation events (caused by radiation
from outside of the detector, such as an object to be imaged). An
individual signal or group of counts of events may be generated or
accumulated over a predetermined accumulation period (e.g., 1
second). For example, a first group of counts may be characterized
by the number of counts at particular energy levels over an initial
time period, a second group of counts may be characterized by the
number of counts at particular energy levels over a subsequent time
period, and so on.
At 1104, counts are obtained for windows distributed about an
energy spectrum. For example, as discussed in connection with 1102,
a signal may be characterized by numbers of counts at particular
energy levels. Windows may be positioned along the spectrum, with
each window defining a range of energy levels, and a separate
accumulation of counts performed for each window over an
accumulation period (e.g., one second). The windows may be disposed
along the spectrum at locations corresponding to different portions
of an expected or nominal signal. For example, in some embodiments
four windows may be disposed proximate an intrinsic portion of the
signal, and four windows disposed proximate a received radiation
portion of the signal. (See FIG. 10 and related discussion.) The
use of such windows disposed along different portions of an energy
spectrum may provide information regarding a spectral signature or
shape of a signal, and provide more information than just an
identification of a peak location. Additionally or alternatively,
one or more auxiliary windows may be utilized in various
embodiments. It may be noted that the counts may be obtained in
various embodiments for differently sized portions of a detector.
For example, counts may be obtained for a single crystal in some
embodiments or for a block of crystals in other embodiments.
Generally speaking, the more crystals or other units for which
counts are collected, the shorter the accumulation period may be to
collect a statistically significant number of counts. Further,
additionally or alternatively, gain adjustments may be made for
differently sized or apportioned units of a detector, such as a
single crystal or a block of crystals. Accordingly, gain may be
independently adjusted based on a local condition for sub-portions
of a detector.
At 1106, one or more weighted sums are determined. Generally, a
weighted sum may be determined for a given accumulation period by
multiplying the accumulated counts for each window by a
predetermined weighting coefficient corresponding to the particular
window. In the depicted embodiment, three weighted sums are
determined. It may be noted that in various embodiments, individual
events may be independently weighted first and then added to a
running accumulator. Additionally, in various embodiments, a
running count of total events seen may be kept (e.g., for use in
connection with stability metric). At 1108, a fine adjustment
weighted sum is determined. For the fine adjustment weighted sum,
in some embodiments, groups of four windows are disposed about one
or more nominal peak energy levels. The inner windows may have
larger weighting coefficients than the outer windows for each group
of four windows, and the signs of the weighting coefficients may
alter between positive and negative between adjacent windows. At
1108, a coarse adjustment weighted sum is determined. For the
coarse adjustment weighted sum, in some embodiments, one or more
windows on one side of a nominal peak are assigned a negative
weighting coefficient, and one or more windows on an opposite side
of the nominal peak are assigned a positive weighting coefficient.
At 1112, a peak centering weighted sum is determined. The peak
centering weighted sum is an example of a peak analysis metric that
may be used to determine whether or not a measured peak is
relatively centered about a group of windows disposed about a
nominal peak, and/or the relative quality or amount of centering.
In some embodiments, where four windows are disposed about a
nominal peak, for the peak centering weighted sum, the inner
windows may have positive sign weighting coefficients and the outer
windows negative sign weighting coefficients. The peak centering
weighted sum, for example, may be used to select between which of
the fine adjustment or the coarse adjustment will be used to adjust
a gain (or determine if a gain adjustment is appropriate).
At 1114, an adjustment technique is selected. In the depicted
example, a peak analysis metric (e.g., the peak centering weighted
sum determined at 1112) is used to select the adjustment technique.
For example, if the peak centering adjustment weighted sum
satisfies or exceeds a given threshold (indicating that the
measured peak is relatively well centered with respect to the
corresponding group of windows), a fine adjustment technique (e.g.,
using the fine adjustment weighted sum) may be selected. However,
if the peak centering adjustment weighted sum does not satisfy or
exceed the given threshold (indicating that the measured peak is
not relatively well centered with respect to the corresponding
group of windows), a coarse adjustment technique (e.g., using the
coarse adjustment weighted sum) may be selected.
At 1116, a stability metric is determined. Generally, the stability
metric is configured and used to determine the significance of a
determined gain adjustment metric or calculation, and determine
whether or not to adjust the gain based on the significance of the
determined adjustment. The stability metric may be determined using
a determined gain adjustment provided by using the technique
selected at 1114. In the depicted embodiment, at 1118, if the
stability metric indicates the adjustment is not significant, then
the adjustment may not be made, and the process may return to 1104
to obtain counts for a subsequent accumulation period. Further, if
a predetermined number of events (for example, 16000) has been
detected without a significant value in the stability metric, then
a very small gain adjustment (for example, .+-.0.1%) may be made
based on the sign of the stability metric, after which all counters
will be reset. In this manner, the control system remains sensitive
to sudden gain changes. Without such a mechanism, if the detector
had been stable for a long time, it would take significant time for
the stability metric to become sufficiently large to generate an
adjustment if a sudden gain change should occur due to a change in
count rate, temperature, supply voltage or other external
factor.
If the adjustment is determined to be significant, the method may
proceed to 1120, with the gain adjusted at 1120. It may be noted
that the gain may be adjusted by adjusting a voltage supplied to
the detector (e.g., a voltage supplied to a particular block of the
detector), or may be adjusted virtually in firmware or software.
For example, in the illustrated embodiments, at 1122, the gain is
adjusted virtually by adjusting the values of measured or detected
energy levels received from a detector unit.
Additional events may be acquired and analyzed, with appropriate
adjustments made to the gain during an imaging process as discussed
herein. Events may be passed along for image processing after they
are analyzed. Generally, after a gain adjustment is made, that
particular gain value will be utilized for subsequent events until
another gain adjustment is determined appropriate as discussed
herein. At 1126, an image is reconstructed using information
collected during the scan.
FIG. 12 provides a flowchart of a method 1200 (e.g., for tracking
an energy peak and/or adjusting a gain of a detection system) in
accordance with various embodiments. The detection system, for
example, may be configured for use with a PET imaging system. The
method 1200, for example, may employ, include, or relate to
structures or aspects of various embodiments discussed herein. In
various embodiments, certain steps may be omitted or added, certain
steps may be combined, certain steps may be performed
simultaneously, certain steps may be performed concurrently,
certain steps may be split into multiple steps, certain steps may
be performed in a different order, or certain steps or series of
steps may be re-performed in an iterative fashion. In various
embodiments, portions, aspects, and/or variations of the method
1200 may be used as one or more algorithms (e.g., software modules
or other instructions stored on a tangible and non-transitory
computer readable medium utilizing or based on the one or more
algorithms) to direct hardware (e.g., processing unit 130 or
portion thereof) to perform one or more operations described
herein.
At 1202, intrinsic radiation events from a detector are obtained.
The intrinsic radiation events may be obtained during an initial
start-up period of a detector. For example, an imaging system may
be activated, but an object to be imaged may not yet be present in
the field of view of the detector. Accordingly, radiation counts
obtained via the detector may correspond to intrinsic radiation,
with little or no radiation detected from a surrounding
environment.
At 1204, the gain is adjusted based on the intrinsic radiation. For
example, an obtained signal may be compared with an expected or
nominal signal and the gain adjusted so that the shape of the
spectrum of the obtained signal more closely matches the expected
shape of the spectrum of the expected or nominal signal based on
known intrinsic radiation sources within the detector (e.g.,
Lu-176). Using various embodiments of gain adjustment disclosed
herein, it has been found that a gain adjustment may effectively
adjust the measured signal to sufficiently track the expected or
nominal signal within ten seconds or less for initial gain errors
up to 10%, and using only intrinsic radiation. Accordingly, a gain
may be efficiently and quickly adjusted for improved accuracy at
the beginning of a scan when an object to be imaged is first
introduced into the field of view of a detector.
At 1206, radiation events are obtained from the detector. For
example, a patient that has been administered a radiopharmaceutical
may be placed within the field of view of the detector.
Accordingly, radiation events (along with the intrinsic events) may
be accumulated and used to determine a gain adjustment as discussed
herein.
At 1208, the gain is adjusted based on the received radiation. The
gain may be adjusted based on the received radiation events as well
as intrinsic radiation events acquired contemporaneously with the
received radiation events. For example, as discussed herein, a gain
adjustment may be determined based on a weighted sum of counts
accumulated by windows associated with intrinsic and received
radiation portions of an energy spectrum.
It should be noted that the various embodiments may be implemented
in hardware, software or a combination thereof. The various
embodiments and/or components, for example, the modules, or
components and controllers therein, also may be implemented as part
of one or more computers or processors. The computer or processor
may include a computing device, an input device, a display unit and
an interface, for example, for accessing the Internet. The computer
or processor may include a microprocessor. The microprocessor may
be connected to a communication bus. The computer or processor may
also include a memory. The memory may include Random Access Memory
(RAM) and Read Only Memory (ROM). The computer or processor further
may include a storage device, which may be a hard disk drive or a
removable storage drive such as a solid state drive, optical drive,
and the like. The storage device may also be other similar means
for loading computer programs or other instructions into the
computer or processor.
As used herein, the term "computer," "controller," and "module" may
each include any processor-based or microprocessor-based system
including systems using microcontrollers, reduced instruction set
computers (RISC), application specific integrated circuits (ASICs),
logic circuits, GPUs, FPGAs, and any other circuitry capable of
executing the functions described herein. The above examples are
exemplary only, and are thus not intended to limit in any way the
definition and/or meaning of the term "module" or "computer."
The computer, module, or processor executes a set of instructions
that are stored in one or more storage elements, in order to
process input data. The storage elements may also store data or
other information as desired or needed. The storage element may be
in the form of an information source or a physical memory element
within a processing machine.
The set of instructions may include various commands that instruct
the computer, module, or processor as a processing machine to
perform specific operations such as the methods and processes of
the various embodiments described and/or illustrated herein. The
set of instructions may be in the form of a software program. The
software may be in various forms such as system software or
application software and which may be embodied as a tangible and
non-transitory computer readable medium. Further, the software may
be in the form of a collection of separate programs or modules, a
program module within a larger program or a portion of a program
module. The software also may include modular programming in the
form of object-oriented programming. The processing of input data
by the processing machine may be in response to operator commands,
or in response to results of previous processing, or in response to
a request made by another processing machine.
As used herein, the terms "software" and "firmware" are
interchangeable, and include any computer program stored in memory
for execution by a computer, including RAM memory, ROM memory,
EPROM memory, EEPROM memory, and non-volatile RAM (NVRAM) memory.
The above memory types are exemplary only, and are thus not
limiting as to the types of memory usable for storage of a computer
program. The individual components of the various embodiments may
be virtualized and hosted by a cloud type computational
environment, for example to allow for dynamic allocation of
computational power, without requiring the user concerning the
location, configuration, and/or specific hardware of the computer
system.
As used herein, a structure, limitation, or element that is
"configured to" perform a task or operation is particularly
structurally formed, constructed, or adapted in a manner
corresponding to the task or operation. For purposes of clarity and
the avoidance of doubt, an object that is merely capable of being
modified to perform the task or operation is not "configured to"
perform the task or operation as used herein. Instead, the use of
"configured to" as used herein denotes structural adaptations or
characteristics, and denotes structural requirements of any
structure, limitation, or element that is described as being
"configured to" perform the task or operation. For example, a
processing unit, processor, or computer that is "configured to"
perform a task or operation may be understood as being particularly
structured to perform the task or operation (e.g., having one or
more programs or instructions stored thereon or used in conjunction
therewith tailored or intended to perform the task or operation,
and/or having an arrangement of processing circuitry tailored or
intended to perform the task or operation). For the purposes of
clarity and the avoidance of doubt, a general purpose computer
(which may become "configured to" perform the task or operation if
appropriately programmed) is not "configured to" perform a task or
operation unless or until specifically programmed or structurally
modified to perform the task or operation.
It is to be understood that the above description is intended to be
illustrative, and not restrictive. For example, the above-described
embodiments (and/or aspects thereof) may be used in combination
with each other. In addition, many modifications may be made to
adapt a particular situation or material to the teachings of the
various embodiments of the invention without departing from their
scope. While the dimensions and types of materials described herein
are intended to define the parameters of the various embodiments of
the invention, the embodiments are by no means limiting and are
exemplary embodiments. Many other embodiments will be apparent to
those of skill in the art upon reviewing the above description. The
scope of the various embodiments of the invention should,
therefore, be determined with reference to the appended claims,
along with the full scope of equivalents to which such claims are
entitled. In the appended claims, the terms "including" and "in
which" are used as the plain-English equivalents of the respective
terms "comprising" and "wherein." Moreover, in the following
claims, the terms "first," "second," and "third," etc. are used
merely as labels, and are not intended to impose numerical
requirements on their objects. Further, the limitations of the
following claims are not written in means-plus-function format and
are not intended to be interpreted based on 35 U.S.C. .sctn.112,
sixth paragraph, unless and until such claim limitations expressly
use the phrase "means for" followed by a statement of function void
of further structure.
This written description uses examples to disclose the various
embodiments of the invention, and also to enable any person skilled
in the art to practice the various embodiments of the invention,
including making and using any devices or systems and performing
any incorporated methods. The patentable scope of the various
embodiments of the invention is defined by the claims, and may
include other examples that occur to those skilled in the art. Such
other examples are intended to be within the scope of the claims if
the examples have structural elements that do not differ from the
literal language of the claims, or if the examples include
equivalent structural elements with insubstantial differences from
the literal language of the claims.
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